Service resource configuration method and device of offline service point, equipment and storage medium

Abstract

The embodiment of the invention discloses a service resource configuration method and device for an offline service point, equipment and a storage medium. The method comprises the following steps: acquiring service information required by a user, user information and a service point expected by the user according to a service queuing request; according to the service information, matching at least one to-be-distributed service point providing a target service corresponding to the service information from all the offline service points, and determining the service point expected by the user as a to-be-distributed service point; according to the service information and the user information, performing service evaluation on each to-be-distributed service point to obtain a current service evaluation value of each to-be-distributed service point relative to the target service; and configuring the optimal service point of the target service for the user according to the service evaluation value of each to-be-distributed service point. The service evaluation value is obtained by performing service evaluation on the to-be-distributed network, and the optimal service point is configured for the user according to the service evaluation value, so that the waiting time of the user can be shortened to a certain extent, and the user experience is improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of big data technology, and in particular to a service resource configuration method, apparatus, device, and storage medium for an offline service point. Background Art

[0002] For some offline service points of enterprises or organizations, such as bank branches and residential service points, they usually provide users with a variety of services. Users can make online appointments or go directly to nearby service points to complete the business they need.

[0003] However, with this traditional method, users are completely free to choose which service point to go to based on their personal habits. This may lead to the concentration of customer flow at some service points, resulting in longer service times, longer waiting times for users to complete their business, and a lower user experience. Summary of the Invention

[0004] The embodiments of the present application provide a service resource configuration method, apparatus, device, and storage medium for an offline service point to shorten user waiting time and improve user experience.

[0005] In a first aspect, an embodiment of the present application provides a method for configuring service resources at an offline service point, the method comprising:

[0006] In response to the user's service queuing request, obtain the user's required service information, user information, and the user's desired service point according to the service queuing request;

[0007] According to the service information, at least one to-be-allocated service point that provides the target service corresponding to the service information is matched from all offline service points, and the user's desired service point is determined as a to-be-allocated service point;

[0008] Perform service evaluation for each service point to be assigned based on service information and user information, and obtain the current service evaluation value of each service point to be assigned relative to the target service;

[0009] According to the service evaluation value of each service point to be allocated, the optimal service point for the target service is configured for the user.

[0010] In a second aspect, an embodiment of the present application provides a service resource configuration device for an offline service point, the device comprising:

[0011] An acquisition module, configured to respond to a user's service queuing request and acquire the user's required service information, user information, and the user's desired service point according to the service queuing request;

[0012] A matching module is used to match at least one to-be-allocated service point that provides a target service corresponding to the service information from all offline service points according to the service information, and determine the user's desired service point as a to-be-allocated service point;

[0013] An evaluation module is used to perform service evaluation for each service point to be assigned based on service information and user information, and obtain the current service evaluation value of each service point to be assigned relative to the target service;

[0014] The configuration module is used to configure the optimal service point for the target service for the user according to the service evaluation value of each service point to be allocated.

[0015] In a third aspect, an embodiment of the present application further provides an electronic device, the electronic device comprising:

[0016] one or more processors;

[0017] a storage device for storing one or more programs,

[0018] When one or more programs are executed by one or more processors, the one or more processors implement the service resource configuration method for an offline service point as provided in any embodiment of the present application.

[0019] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the service resource configuration method for an offline service point as provided in any embodiment of the present application is implemented.

[0020] In a fifth aspect, an embodiment of the present application further provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements a service resource configuration method for an offline service point as provided in any embodiment of the present application.

[0021] The technical solution of the embodiment of the present application responds to the user's service queuing request and obtains the service information, user information, and user's desired service point required by the user according to the service queuing request; matches at least one to-be-allocated service point that provides the target service corresponding to the service information from all offline service points based on the service information, and determines the user's desired service point as a to-be-allocated service point; performs a service evaluation on each to-be-allocated service point based on the service information and user information, and obtains the current service evaluation value of each to-be-allocated service point relative to the target service; and configures the user with the optimal service point for the target service based on the service evaluation value of each to-be-allocated service point. Based on this, by performing a service evaluation on the to-be-allocated network point, obtaining a service evaluation value relative to the target service, and then configuring the optimal service point for the user based on the service evaluation value, the user's waiting time can be shortened to a certain extent, thereby improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A flowchart of a service resource configuration method for an offline service point provided in Example 1 of the present application;

[0023] Figure 2 A schematic diagram of the structure of a service resource configuration device for an offline service point provided in Example 2 of the present application;

[0024] Figure 3 This is a structural diagram of an electronic device provided in Example 3 of the present application. DETAILED DESCRIPTION

[0025] The present application will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are intended only to illustrate the present application and are not intended to limit the present application. It should also be noted that, for ease of description, the accompanying drawings only illustrate portions of the present application, not all of the structures.

[0026] Example 1

[0027] Figure 1 This is a flow chart of the service resource configuration method for offline service points provided in Example 1 of this application, as shown in FIG. Figure 1 As shown, the service resource configuration method for offline service points provided in this embodiment can be applied to a service resource configuration platform for offline service points mounted on a device with data processing capabilities such as a computer, and can be used in conjunction with some application software to achieve a better experience. Specifically, the method may include the following steps:

[0028] Step 101: In response to a user's service queuing request, obtain the user's required service information, user information, and the user's desired service point according to the service queuing request.

[0029] In this step, the service queuing request refers to the request generated when the user queues for a service. The service queuing request can be initiated by the user in the relevant software program of the mobile terminal or at any service point.

[0030] The service number request may include the identification code of the desired service, the user's authorized user ID, the information retrieval type, and the desired service point. It should be noted that both the information retrieval type and the user ID require user authorization to obtain. If the user does not authorize, such information can be set to the default value.

[0031] In addition, the information retrieval type refers to the type of user information that the user has authorized to retrieve, such as user location, user age, etc. It should be noted that the information collected is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with the relevant laws, regulations and standards of the relevant countries and regions, adopt necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0032] The user's desired service point may be a service point selected by the user on the mobile terminal, or may be the service point where the user is currently located (when initiated on-site).

[0033] Step 102: According to the service information, at least one to-be-allocated service point providing the target service corresponding to the service information is matched from all offline service points, and the user's desired service point is determined as a to-be-allocated service point.

[0034] In this step, the service support types of all offline service points can be obtained first; then for any offline service point, it is determined whether the corresponding service support type includes the target service corresponding to the service information; if included, the offline service point is determined as the service point to be allocated.

[0035] The service support type can be used to directly determine whether the services supported by the offline service point include the target service, thereby improving the matching speed.

[0036] In a specific example, a service point can be an offline branch of a bank. Each branch may pre-store service support types, i.e., the services it supports. The service information may include a target service type identifier. For each offline branch, the stored service support types are searched to determine whether the target service type identifier exists. If so, the offline branch supports the target service and can provide it.

[0037] Step 103: Perform service evaluation for each service point to be allocated based on the service information and user information to obtain the current service evaluation value of each service point to be allocated relative to the target service.

[0038] In this step, the service status of the target service in each service point to be allocated can be obtained based on the service information, and the distance information of each service point to be allocated can be determined based on the user information. For any service point to be allocated, the service status and distance information are input into the pre-trained service allocation model, and the service evaluation value of the service point to be allocated relative to the target service output by the service allocation model is obtained.

[0039] By using the service allocation model, the service evaluation value of the service point to be allocated relative to the target service can be more accurately realized to identify the current user's preference for the target service at the service point to be allocated.

[0040] Among them, the service status may include the total number of service resources (the number of points that can handle the service at the same time), the number of people at the current service point, the customer waiting time, etc., and the user information may include customer star rating, customer age, customer gender, customer location, etc.

[0041] The geographical distance or navigation distance may be calculated based on the location of the user and the location of the service point to be allocated, and the calculated distance value may be used as the distance information.

[0042] In addition, for the service allocation model, this embodiment can use the service point service history data to train the service allocation model in advance, and periodically update the service allocation model for training; specifically, the pre-built service allocation model can be abstracted into a multi-factor joint decision-making calculation model using a tree structure; the abstracted calculation model can be genetically transformed and trained using the service point service history data, and the training of the service allocation model is completed when the iteration termination condition is met.

[0043] By abstracting the model into a tree structure, the model can be simplified into a computational model for multi-factor joint decision-making, which can speed up the training of the model.

[0044] In a specific example, taking bank branches as an example, you can obtain customer service history data for all branches in a certain area over the past N days, where N is a configurable parameter for the business and can be adjusted according to the business volume of the area. The principle is to ensure that the amount of customer service data over N days is sufficient. Specific service history data can be referenced but not limited to the following:

[0045] Basic branch service information: such as the types of services available at the branch, the average processing time for each service type, the statistical mean of the time distance between branches, the physical distance between branches, and the total number of branch service resources (including customer service personnel, equipment, etc.);

[0046] Customer information: such as whether the customer is a customer of our bank, type of business handled, customer star rating, customer gender, customer age, etc.

[0047] Based on the above data, we use the optimization calculation method to model and train the network service resource allocation algorithm, which can specifically include:

[0048] Set the optimization objective function. The optimal function must be set by the regional business experts. Factors that affect the customer service experience are taken into consideration, including the total customer service time T (including walking time), the customer's walking distance L, the customer's star rating S, the customer's gender M, and the customer's age A. The objective function for evaluating the optimization effect of customer service resource allocation is specifically set to: max f(x) = ∑[(k1*T)+(K2*L)+(k3*S)+(k4*M)+(k5*A)]*T. Among them, k1 to k5 represent the proportion parameters of each influencing priority. The optimization goal is to optimize the total time after considering the weighted factors of each factor (total customer service time T (including walking time), customer's walking distance L, customer star rating S, customer gender M, and customer age A) under the total input flow.

[0049] In this embodiment, no constraints are used.

[0050] Design an optimization algorithm: Using genetic programming, the branch resource allocation model is abstracted into a multi-factor decision-making computational model using a tree structure. The decision-making variables include the total number of branch service resources, the number of current branch customers, customer star rating, customer age, customer gender, customer wait time, and customer travel distance. These variables are configured in a configuration file, and dynamic addition and deletion of variables is supported. Computational elements include the aforementioned decision variables, operators (such as +, -, *, / , sin, and log), and constants (0-9).

[0051] Then train the model: first randomly initialize a group of feasible solutions (N, N can be set), each feasible solution is an individual, that is, use the above elements to generate a calculation model, the calculation model inputs the above variable information, and calculates and outputs a service ranking score for each branch that matches the customer's business. The score is ultimately used to evaluate and rank the customer's choice of the best branch.

[0052] Then, the fitness probability of each feasible solution, or individual, is calculated. Substituting these feasible solutions into the customer service data for each branch, the customer service score for each branch is calculated. Based on this score, customer service branches are assigned. The relevant data calculation results are obtained according to the objective function set above. The fitness ti is calculated by sorting the results. A larger value indicates a greater fitness. Therefore, the fitness probability of each individual, ki, is calculated as ti / ∑ti.

[0053] Then select the individuals to be evolved. According to the fitness probability results, select the top X (X can be set) individuals as the individuals to be evolved.

[0054] Then perform evolutionary operations. The operation types include: replication, crossover, and mutation. Replication operation: Select the K individuals with the highest fitness (K can be set) and retain them for the next iteration. Crossover operation: Select two individuals from the above X individuals through the roulette wheel algorithm and exchange part of the tree structures of the two individuals. Mutation operation: Randomly select Z individuals (Z can be set) and perform random transformations on their tree structures.

[0055] Start a new round of iteration. Repeat the above steps to start a new round of genetic evolutionary operations. Control according to the iteration times set by experience, and stop the evolutionary iteration after reaching the specified number of times.

[0056] Among them, the termination of training can be achieved by setting the termination condition P1, and P1 is the number of iteration terminations. Judge the termination condition. Judge the number of evolutionary iteration rounds. If the iteration round number > P1, then judge further. If the iteration round number < P1, then continue the evolutionary iteration. If the iteration round number > P1, record the maximum value D of the objective function in the individuals of this round of iteration and the maximum value D' of the objective function in the individuals of the next round of iteration. If D > D', then terminate the iteration. If D < D', then continue the iteration until D > D' and then terminate the iteration.

[0057] In addition, when periodically updating and training the service allocation model, when the model update period is reached, obtain the current training samples and the previous training samples of the service allocation model; if there are differences between the current training samples and the previous training samples, use the current training samples to update and train the service allocation model.

[0058] Through the update training, the model can be more adapted to the current service resources, and further improve the accuracy of the model evaluation.

[0059] In a specific example, the update period parameter P2 of the network point customer service allocation algorithm can be obtained. If the last training completion date of the network point customer service allocation algorithm - the current date > P2, then it is necessary to call the allocation algorithm retraining module to update the model.

[0060] Then obtain the configuration variable parameters of the network point customer service allocation algorithm, and judge whether there are changes in the algorithm training input variables. If there are changes, then it is necessary to call the allocation algorithm retraining module to update the model.

[0061] If the allocation algorithm reaches the retraining period or there are changes in the variable parameters, then call the retraining module to update and train the model.

[0062] Step 104: Configure the optimal service point for the target service for the user according to the service evaluation value of each service point to be allocated.

[0063] In this step, the service points to be allocated can be sorted from high to low according to their respective service evaluation values; it is determined whether the service point to be allocated ranked first is the user's expected service point. If so, the user's expected service point is configured as the optimal service point for the target service.

[0064] By sorting, the optimal service point can be determined more intuitively.

[0065] In a specific example, the outlets are sorted according to their scores, and the result ranked first is judged. If the outlet ranked first is the in-store outlet where the customer goes or the outlet where the customer chooses to handle the business online, the next step of the resource service allocation process within the outlet will be carried out. If the outlet ranked first is an outlet other than the in-store outlet, the customer will be prompted to go to the nearest outlet to handle the business faster, and the outlet location information will be provided at the same time.

[0066] In this embodiment, in response to a user's service queuing request, the user's required service information, user information, and desired service point are obtained based on the service queuing request. Based on the service information, at least one to-be-assigned service point that provides the target service corresponding to the service information is matched from all offline service points, and the user's desired service point is determined as the to-be-assigned service point. Based on the service information and user information, a service evaluation is performed on each to-be-assigned service point to obtain the current service evaluation value of each to-be-assigned service point relative to the target service. Based on the service evaluation value of each to-be-assigned service point, the optimal service point for the target service is configured for the user. Based on this, by performing a service evaluation on the to-be-assigned network points to obtain a service evaluation value relative to the target service, and then configuring the optimal service point for the user based on this service evaluation value, the user's waiting time can be shortened to a certain extent, thereby improving the user experience.

[0067] Example 2

[0068] Figure 2 This is a structural diagram of a service resource configuration device for an offline service point provided in Example 2 of this application. The service resource configuration device for an offline service point provided in this embodiment of the application can execute the service resource configuration method for an offline service point provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects of the execution method. The device can be implemented in software and / or hardware, such as Figure 2 As shown, the service resource configuration device of the offline service point specifically includes: an acquisition module 201, a matching module 202, an evaluation module 203, and a configuration module 204.

[0069] The acquisition module is used to respond to the user's service number request and obtain the service information required by the user, user information and the user's desired service point according to the service number request;

[0070] A matching module is used to match at least one to-be-allocated service point that provides a target service corresponding to the service information from all offline service points according to the service information, and determine the user's desired service point as a to-be-allocated service point;

[0071] An evaluation module is used to perform service evaluation for each service point to be assigned based on service information and user information, and obtain the current service evaluation value of each service point to be assigned relative to the target service;

[0072] The configuration module is used to configure the optimal service point for the target service for the user according to the service evaluation value of each service point to be allocated.

[0073] Furthermore, the matching module includes:

[0074] A first acquisition unit is used to acquire the service support type of each offline service point;

[0075] a judgment unit, configured to judge, for any offline service point, whether the corresponding service support type includes a target service corresponding to the service information;

[0076] A determining unit is configured to, if included, determine the offline service point as the service point to be allocated.

[0077] Furthermore, the assessment module includes:

[0078] A second acquiring unit is configured to acquire the service status of the target service in each to-be-allocated service point according to the service information, and to determine the distance information of each to-be-allocated service point according to the user information;

[0079] The evaluation unit is used to input the service status and distance information of any service point to be allocated into a pre-trained service allocation model, and obtain the service evaluation value of the service point to be allocated relative to the target service output by the service allocation model.

[0080] Furthermore, the device also includes:

[0081] A model training module is used to pre-train the service allocation model using the service point service history data and to periodically update the service allocation model;

[0082] The model training module includes:

[0083] An abstraction unit, used to abstract the pre-built service allocation model into a multi-factor joint decision-making calculation model using a tree structure;

[0084] The training unit is used to perform genetic training on the abstracted computing model using the service history data of the service points, and complete the training of the service allocation model when the iteration termination condition is met.

[0085] Furthermore, the model training module includes:

[0086] A sample acquisition unit, configured to acquire the current training sample and the previous training sample of the service allocation model when the model update cycle is reached;

[0087] The updating training unit is used to update the service allocation model using the current training sample if there is a difference between the current training sample and the previous training sample.

[0088] Furthermore, the configuration module includes:

[0089] A sorting unit, configured to sort the service points to be allocated from high to low according to the service evaluation value of each service point to be allocated;

[0090] The configuration unit is used to determine whether the first-ranked service point to be allocated is the user's desired service point. If so, the user's desired service point is configured as the optimal service point for the target service.

[0091] Example 3

[0092] Figure 3 This is a structural diagram of an electronic device provided in Example 3 of the present application, such as Figure 3 As shown, the electronic device includes a processor 310, a memory 320, an input device 330 and an output device 340; the number of processors 310 in the electronic device can be one or more. Figure 3 In the figure, a processor 310 is used as an example; the processor 310, memory 320, input device 330 and output device 340 in the electronic device can be connected via a bus or other means. Figure 3 The bus connection is taken as an example.

[0093] The memory 320, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the service resource configuration method for offline service points in the embodiments of the present invention. The processor 310 executes the software programs, instructions, and modules stored in the memory 320 to execute various functional applications and data processing of the electronic device, thereby implementing the service resource configuration method for offline service points described above:

[0094] In response to the user's service queuing request, obtain the user's required service information, user information, and the user's desired service point according to the service queuing request;

[0095] According to the service information, at least one to-be-allocated service point that provides the target service corresponding to the service information is matched from all offline service points, and the user's desired service point is determined as a to-be-allocated service point;

[0096] Perform service evaluation for each service point to be assigned based on service information and user information, and obtain the current service evaluation value of each service point to be assigned relative to the target service;

[0097] According to the service evaluation value of each service point to be allocated, the optimal service point for the target service is configured for the user.

[0098] The memory 320 may primarily include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function; the data storage area may store data created based on the use of the terminal, etc. Furthermore, the memory 320 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 320 may further include a memory remotely located relative to the processor 310, and these remote memories may be connected to the electronic device via a network. Examples of the aforementioned networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0099] Example 4

[0100] The fourth embodiment of the present application further provides a storage medium containing computer-executable instructions. When the computer-executable instructions are executed by a computer processor, the computer-executable instructions are used to execute a service resource configuration method for an offline service point. The method includes:

[0101] In response to the user's service queuing request, obtain the user's required service information, user information, and the user's desired service point according to the service queuing request;

[0102] According to the service information, at least one to-be-allocated service point that provides the target service corresponding to the service information is matched from all offline service points, and the user's desired service point is determined as a to-be-allocated service point;

[0103] Perform service evaluation for each service point to be assigned based on service information and user information, and obtain the current service evaluation value of each service point to be assigned relative to the target service;

[0104] According to the service evaluation value of each service point to be allocated, the optimal service point for the target service is configured for the user.

[0105] Of course, the storage medium containing computer-executable instructions provided in an embodiment of the present application is not limited to the above method operations, and its computer-executable instructions can also execute related operations in the service resource configuration method of the offline service point provided in any embodiment of the present application.

[0106] Through the above description of the implementation methods, those skilled in the art can clearly understand that the present application can be implemented with the help of software and necessary general-purpose hardware, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer's floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of each embodiment of the present application.

[0107] It is worth noting that in the embodiments of the above-mentioned device, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application.

[0108] Example 5

[0109] This embodiment provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the service resource configuration method for an offline service point provided in any embodiment of this application. The method may specifically include:

[0110] In response to the user's service queuing request, obtain the user's required service information, user information, and the user's desired service point according to the service queuing request;

[0111] According to the service information, at least one to-be-allocated service point that provides the target service corresponding to the service information is matched from all offline service points, and the user's desired service point is determined as a to-be-allocated service point;

[0112] Perform service evaluation for each service point to be assigned based on service information and user information, and obtain the current service evaluation value of each service point to be assigned relative to the target service;

[0113] According to the service evaluation value of each service point to be allocated, the optimal service point for the target service is configured for the user.

[0114] Note that the above are only preferred embodiments of the present application and the technical principles employed. Those skilled in the art will understand that the present application is not limited to the specific embodiments herein, and that various obvious changes, readjustments, and substitutions can be made by those skilled in the art without departing from the scope of protection of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments and may include many other equivalent embodiments without departing from the scope of the present application. The scope of the present application is determined by the scope of the appended claims.

Claims

1. A service resource configuration method for an offline service point, characterized in that: The method comprises: In response to a user's service queuing request, obtaining service information required by the user, user information, and a user's desired service point according to the service queuing request; According to the service information, matching at least one to-be-allocated service point that provides the target service corresponding to the service information from all offline service points, and determining the user's desired service point as a to-be-allocated service point; Performing a service evaluation for each of the to-be-allocated service points based on the service information and user information to obtain a current service evaluation value of each of the to-be-allocated service points relative to the target service; The optimal service point for the target service is configured for the user according to the service evaluation value of each of the to-be-allocated service points.

2. The method according to claim 1, characterized in that The step of matching at least one to-be-allocated service point that provides the target service corresponding to the service information from all offline service points according to the service information includes: Get the service support types of all offline service points; For any offline service point, determining whether the corresponding service support type includes the target service corresponding to the service information; If included, the offline service point is determined as the service point to be allocated.

3. The method according to claim 1, characterized in that The performing of service evaluation for each of the to-be-allocated service points according to the service information and the user information to obtain a current service evaluation value of each of the to-be-allocated service points relative to the target service includes: Acquire the service status of the target service in each of the to-be-allocated service points according to the service information, and determine the distance information of each of the to-be-allocated service points according to the user information; For any service point to be allocated, the service status and the distance information are input into a pre-trained service allocation model, and a service evaluation value of the service point to be allocated relative to the target service output by the service allocation model is obtained.

4. The method according to claim 3, characterized in that The method further comprises: Pre-training a service allocation model using service point service history data, and periodically updating and training the service allocation model; The pre-training of the service allocation model using the service point service history data includes: The pre-built service allocation model is abstracted into a multi-factor joint decision-making calculation model using a tree structure; The abstracted computing model is genetically trained using the service point service history data, and the training of the service allocation model is completed when an iteration termination condition is met.

5. The method according to claim 4, characterized in that The periodically updating and training the service allocation model includes: When the model update cycle is reached, obtaining the current training sample and the previous training sample of the service allocation model; If there is a difference between the current training sample and the previous training sample, the service allocation model is updated and trained using the current training sample.

6. The method according to claim 1, characterized in that The configuring, for the user, an optimal service point for the target service based on the service evaluation value of each of the to-be-allocated service points includes: Sort the service points to be allocated from high to low according to the service evaluation value of each of the service points to be allocated; It is determined whether the first service point to be allocated is the user's desired service point. If so, the user's desired service point is configured as the optimal service point for the target service.

7. A service resource configuration device for an offline service point, characterized in that: The device comprises: An acquisition module, configured to respond to a user's service queuing request and acquire the service information required by the user, user information, and the user's desired service point according to the service queuing request; A matching module is configured to match, based on the service information, at least one to-be-allocated service point that provides the target service corresponding to the service information from all offline service points, and determine the user's desired service point as a to-be-allocated service point; An evaluation module, configured to perform a service evaluation for each of the to-be-allocated service points based on the service information and user information, and obtain a current service evaluation value of each of the to-be-allocated service points relative to the target service; A configuration module is configured to configure an optimal service point for the target service for the user according to the service evaluation value of each of the service points to be allocated.

8. An electronic device, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the service resource configuration method for an offline service point as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the service resource configuration method for an offline service point as described in any one of claims 1 to 6 is implemented.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the service resource configuration method for an offline service point according to any one of claims 1 to 6 is implemented.

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